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NN
2006
Springer
153views Neural Networks» more  NN 2006»
15 years 1 months ago
An incremental network for on-line unsupervised classification and topology learning
This paper presents an on-line unsupervised learning mechanism for unlabeled data that are polluted by noise. Using a similarity thresholdbased and a local error-based insertion c...
Shen Furao, Osamu Hasegawa
ISCI
2007
170views more  ISCI 2007»
15 years 1 months ago
Automatic learning of cost functions for graph edit distance
Graph matching and graph edit distance have become important tools in structural pattern recognition. The graph edit distance concept allows us to measure the structural similarit...
Michel Neuhaus, Horst Bunke
AAAI
2010
15 years 11 hour ago
Non-I.I.D. Multi-Instance Dimensionality Reduction by Learning a Maximum Bag Margin Subspace
Multi-instance learning, as other machine learning tasks, also suffers from the curse of dimensionality. Although dimensionality reduction methods have been investigated for many ...
Wei Ping, Ye Xu, Kexin Ren, Chi-Hung Chi, Shen Fur...
ICIP
2010
IEEE
14 years 12 months ago
Texture classification via patch-based sparse texton learning
Texture classification is a classical yet still active topic in computer vision and pattern recognition. Recently, several new texture classification approaches by modeling textur...
Jin Xie, Lei Zhang, Jane You, David Zhang
ICMLA
2009
14 years 11 months ago
Alive on Back-feed Culprit Identification via Machine Learning
We describe an application of machine learning techniques toward the problem of predicting which network protector switch is the cause of an Alive on Back-Feed (ABF) event in the ...
Bert C. Huang, Ansaf Salleb-Aouissi, Philip Gross